Ep 185: AKNF - Efficient Amazon Ads Spend Through Deep Segmentation with Clifford and Rob from Pilothouse's Amazon squad

Mar 18, 2022

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Rob and Clifford from Pilothouse recently attended a large Amazon vendor show, and the word everyone kept bringing up was efficiency. Everyone's looking for their Amazon Ad Spend to be more efficient.

This podcast explains how to achieve Amazon Ads efficiency this through deep product listing segmentation:

Work with Pilothouse Amazon ➝ https://pilothouse.co

As Clifford details:

Recently we've been REALLY segmenting keywords hard - we used to mention this as something to do for Sponsored Brand, but we're leaning into it for Sponsored Products as well. I'll lean into the classic example. Let's say we're Nike - selling a new, red and white basketball shoe.Our approach a year ago for sponsored products would have been something along the lines of:

Build a generic keyword campaign ('basketball shoes')
Build a competitor keyword campaign ('adidas basketball shoes')
Build a competitor ASIN campaign
Build a branded keyword campaign
Build a branded asin campaign

If there was some obvious segmentation we may do some ad groups within those campaigns. But we've now evolved that strategy to segment... everything. Instead of a branded keyword campaign - we'd have:

Branded generic keywords ("Nike")
Branded generic shoe keywords ("Nike shoes")
Branded Nike basketball shoe keywords ("Nike basketball shoes")
Branded Nike high-top shoe keywords ("Nike high-tops")
Branded Nike Color keywords ("Red Nikes")
Branded Nike Material keywords ("Polymer Rubber Nikes")

So then the next question is... why? Why put in all this effort and time to segment them?

1st is efficiency - customers shopping for "Nike" aren't as interested in these shoes as a customer shopping for "Nike basketball shoes" - so we'll likely have different efficiency targets for these campaigns, and, thus, move bids differently depending on that.

2nd is for general brand knowledge/data cleanliness - it would be a pain to look inside different campaigns and pull out what keywords are performing and whatnot. This way, it can be seen at a glance really quickly.

3rd is something we came to learn over time - that campaigns with too many keywords, just seem not to perform as well (roughly 50-60+), so limiting it seems to help with delivery. There's a few more reasons, like difference is placement percentages, different negative keywords, etc.

So - that's just the branded keywords - we'd do similar segmentation for all the generic keywords, competitor keywords, competitor ASINs, etc.

And we'd build that entire suite of campaigns out for each individual product - and also for each ad type (Sponsored Product, Sponsored Brand to Store, Sponsored Brand Video, and Sponsored Display)

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